A method for predicting the service life of an arc extinguishing device of a low voltage circuit breaker

Abstract

The application discloses a kind of low-voltage circuit breaker's arc extinguishing device life prediction method, arc extinguishing chamber is divided into left side arc starting area, middle movement area and right side arc extinguishing area along arc movement path three functional sections;Special multi-modal sensor group is configured for each section, respectively collect the physical signal related to the core degradation mechanism of each section;Characteristic parameters including arc starting phase angle, arc movement speed, gas pressure rising rate are extracted from signal, and the efficiency coefficient of each section is calculated;Based on efficiency coefficient and cumulative stress, an independent exponential decay model is established for each section to calculate its cumulative degradation amount;Finally, the maximum cumulative degradation amount in three sections is taken as the system health status index, and the accurate prediction of remaining life is realized.The application solves the problem that the prediction object is fuzzy and the fault cannot be located in the traditional method, realizes the leap from overall early warning to section accurate diagnosis, and provides an effective means for predictive maintenance of low-voltage circuit breaker.

Description

Technical Field

[0001] This invention relates to the field of power equipment condition monitoring and fault prediction technology, and in particular to a method for predicting the lifespan of a low-voltage circuit breaker arc extinguishing device. Background Technology

[0002] Low-voltage circuit breakers are core components in power distribution systems that enable control and protection functions. Their breaking capacity and reliability directly affect the safety and stability of the power supply network. The electrical life of a circuit breaker is primarily affected by the erosion and wear of its contacts and arc-extinguishing devices during arc interruption.

[0003] Existing technologies primarily assess overall lifespan, represented by contact wear, by monitoring cumulative arc energy. These methods have the following inherent limitations: The prediction object is vague: the circuit breaker is regarded as a black box, and it is impossible to distinguish the contribution of contact erosion and arc extinguishing device performance degradation to the overall lifespan. Limited sensing dimension: It usually relies only on two electrical parameters, arc voltage and current, and cannot fully capture the state changes inside the arc extinguishing chamber; Poor model adaptability: It uses a fixed cumulative energy threshold as the lifespan termination criterion, ignoring the individual characteristic differences caused by manufacturing tolerances and material batch differences.

[0004] Therefore, there is an urgent need in this field for a life prediction method that can perform targeted monitoring of arc extinguishing devices, reflect their internal state using multi-dimensional information, and has adaptive learning capabilities. Summary of the Invention

[0005] The present invention aims to overcome the above-mentioned defects of the prior art and provide a method and system for predicting the remaining life of an arc extinguishing device that is accurate, reliable and capable of fault location.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for predicting the lifespan of an arc-extinguishing device in a low-voltage circuit breaker, characterized by comprising the following steps: (a) The arc-extinguishing chamber is divided into three functionally independent sections along the direction of arc movement: the left section corresponds to the arc-starting area where the moving and stationary contacts separate, the middle section corresponds to the arc movement and energy transfer area, and the right section corresponds to the arc extinguishing and pressure building area. (b) Deploy a dedicated sensor array in each section, wherein the left section is configured with a sensor array for monitoring arc initiation characteristics, the middle section is configured with a sensor array for tracking arc motion characteristics, and the right section is configured with a sensor array for detecting arc extinction characteristics. (c) Collect the output signals of each sensor during each interruption operation and extract the feature parameters of each segment. The feature parameters related to the arc initiation process are extracted from the left segment, the feature parameters related to the arc movement process are extracted from the middle segment, and the feature parameters related to the arc extinguishing process are extracted from the right segment. (d) Based on the characteristic parameters of each segment, calculate the efficiency coefficient of the left segment, the efficiency coefficient of the middle segment, and the efficiency coefficient of the right segment respectively; (e) Establish an independent performance degradation model for each segment and calculate the cumulative degradation of each segment; (f) Take the maximum value of the cumulative degradation of the three sections as the cumulative degradation of the system, predict the remaining lifetime based on the comparison between the cumulative degradation of the system and the failure threshold, and identify the section with the most severe degradation.

[0007] The invention further includes a sensor group in the left section comprising a high-frequency current transformer and a high-speed optical sensor, wherein the high-frequency current transformer is mounted on a conductive circuit adjacent to the moving and stationary contacts, and the high-speed optical sensor is aligned with the contact separation gap through an optical observation window.

[0008] The present invention further provides that the sensor group in the intermediate section includes a Hall sensor array and an ultraviolet sensor, wherein the Hall sensor array is arranged at a specific interval along the direction of arc movement, and the ultraviolet sensor is installed at an observation window that can cover the area of ​​the arc-extinguishing grid.

[0009] The present invention further provides that the sensor group in the right section includes a dynamic pressure sensor and an acoustic emission sensor, wherein the dynamic pressure sensor is connected to the arc-extinguishing chamber cavity through a pressure guiding hole, and the acoustic emission sensor is installed on the surface of the outer shell of the arc-extinguishing chamber.

[0010] The present invention further provides that the characteristic parameters of the left segment include the arc initiation phase angle and the initial arc energy, wherein the arc initiation phase angle is obtained by analyzing the phase relationship between the current signal and the voltage signal, and the initial arc energy is obtained by integrating the arc energy within a specific time window in the initial stage of arc initiation.

[0011] The present invention further provides that the characteristic parameters of the intermediate section include the arc movement speed and the dwell time within the section, wherein the arc movement speed is obtained by analyzing the arc position change rate, and the dwell time within the section is obtained by calculating the length of time the arc exists within the section.

[0012] The present invention further provides that the characteristic parameters of the right-side section include the rate of increase of air pressure and the sharpness of arc extinction, wherein the rate of increase of air pressure is obtained by analyzing the rate of change of air pressure signal, and the sharpness of arc extinction is obtained by performing frequency domain analysis on acoustic emission signal.

[0013] The present invention further provides that the efficiency coefficient calculation adopts a weighted fusion method, which normalizes each feature parameter and then fuses them according to a predetermined weight to obtain an efficiency coefficient value between 0 and 1.

[0014] The present invention further provides that the performance degradation model adopts an exponential degradation form, which correlates the section performance coefficient with the exponential degradation relationship of the section cumulative stress, and obtains the linearized cumulative degradation amount by taking the natural logarithm.

[0015] The present invention further provides that the remaining lifetime prediction adopts a proportional calculation method, which divides the difference between the cumulative degradation amount of the system and the failure threshold by the failure threshold to obtain the remaining lifetime percentage. When the cumulative degradation amount of a certain segment is identified to reach the maximum value, specific early warning information for that segment is output.

[0016] The beneficial effects of this invention are: This invention realizes a dedicated life prediction for arc extinguishing devices, with high prediction accuracy and early warning time. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the process of an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following drawings indicate similar items; therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0019] In existing technologies, low-voltage circuit breakers, as core protection components of power distribution systems, rely primarily on the cumulative calculation of overall arcing energy for electrical life assessment. Traditional methods monitor circuit breakers as a single unit, collecting only arc voltage and current signals as the basis for judgment. This method cannot distinguish the degradation states of different functional areas within the arc-extinguishing device, leading to discrepancies between predicted results and actual physical damage. Under complex power grid conditions, the stress experienced by different areas within the arc-extinguishing chamber varies significantly, making it difficult for a uniform threshold model to adapt to individual differences arising from different manufacturing batches or material properties.

[0020] To address the aforementioned issues, those skilled in the art have noted the functional differences between different regions within the arc-extinguishing device, such as the high-temperature ablation in the arc-initiating region, the energy transfer in the moving region, and the pressure impact in the arc-extinguishing region. Analysis revealed that refining the monitoring target from the overall device to functional areas can effectively improve the accuracy of state perception. Based on this, the inventors proposed dividing the arc-extinguishing chamber into three functionally independent sections and deploying dedicated sensor groups for each section's physical characteristics. By establishing independent degradation models for each section, the degradation areas can be accurately located, and the lifetime prediction parameters can be dynamically adjusted.

[0021] Therefore, this application proposes a method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker, comprising the following steps: dividing the arc-extinguishing chamber into three functionally independent sections along the arc movement direction; deploying a dedicated sensor group in each section; collecting the output signals of each sensor during each interruption operation and extracting the characteristic parameters of each section; calculating the efficiency coefficient based on the characteristic parameters of each section; establishing an independent efficiency decay model for each section and calculating the cumulative degradation; taking the maximum value of the cumulative degradation among the three sections as the system cumulative degradation; predicting the remaining lifespan based on the comparison between the system cumulative degradation and the failure threshold, and identifying the section with the most severe degradation.

[0022] The three functionally independent sections refer to physical spatial regions divided according to the arc's trajectory. The left section corresponds to the starting position of the arc generated by the separation of the moving and stationary contacts, the middle section corresponds to the arc's movement path between the arc-extinguishing grid plates, and the right section corresponds to the pressure chamber where the arc is finally extinguished. This division can be achieved through the internal structural features of the arc-extinguishing chamber, for example, using the contact separation point as the left boundary and the end of the arc-extinguishing grid plate as the middle dividing point.

[0023] A dedicated sensor array refers to a combination of sensing devices configured according to the functional characteristics of each section. For example, a high-frequency current transformer can be used in the left section to capture the sudden current change at the moment of arc ignition; a Hall effect sensor array can be used in the middle section to monitor the arc's trajectory; and a dynamic pressure sensor can be used in the right section to detect pressure changes during the arc extinction phase. The sensor installation locations must maintain a physical correspondence with the monitored target area.

[0024] Feature parameter extraction refers to separating physical quantities directly related to the regional function from sensor signals. For example, extracting the arc initiation phase angle in the left segment reflects the electrical state at the moment of contact separation; extracting the arc dwell time in the middle segment reflects the energy transfer efficiency; and extracting the air pressure rise rate in the right segment reflects the arc extinguishing intensity. Signal processing can be achieved using time-frequency analysis or numerical integration methods.

[0025] When extracting features from the left segment, the system continuously monitors the power supply voltage signal and CT signal. When the value exceeds a preset threshold (e.g., 10 A / μs), it is recorded as the arc initiation moment. .calculate Time difference with the previous voltage zero crossing The formula for calculating its starting phase angle is as follows: ,in For the power grid frequency, This represents the time difference between the arc initiation moment and the voltage zero-crossing point. The initial arc energy is then calculated using the following formula: ;in This is the instantaneous value of the arc voltage. This is the instantaneous value of the arc current. This is the moment when the arc begins.

[0026] Simultaneously, feature extraction is performed on the intermediate section, and the arc position is inverted using Hall sensor signals, i.e., the outputs of the two Hall sensors. and Before the system is put into use, calibration is required: move a known simulated arc source along the X direction and record the position x corresponding to each location. and ratio To form a calibration curve During online measurement, calculations are performed in real time. By querying the calibration curve, you can obtain... The calculation method is as follows: ,in The ratio of magnetic field strength, and The signal is from a Hall sensor. , where a, b, and c are the amplitude coefficient, attenuation coefficient, and offset coefficient, respectively; the value range of a is 5.0 ~ 15.0; the value range of b is 0.4 ~ 1.2; and the value range of c is 0.05 ~ 0.3.

[0027] The specific values ​​of a, b, and c were obtained by collecting data at different locations through calibration experiments. The ratio of sensor signals under the following conditions And a nonlinear least squares method is used to apply the exponential decay model. By performing a fitting process, the specific values ​​of the coefficients are finally obtained.

[0028] Subsequently The instantaneous velocity is obtained by numerical differentiation of the sequence. Then calculate its average value over the middle time interval. Calculate the average arc velocity: in, This refers to the point in time when the electric arc has just entered the boundary of the middle section. This refers to the point in time when the electric arc has just left the boundary of the middle section. The position of the electric arc calculated at the kth sampling point; The sampling interval is denoted as .

[0029] When extracting features from the right segment, the pressure signal is numerically differentiated, and the pressure rise rate is calculated using the following formula: The method for calculating the arc extinction sharpness is as follows: Acquire the raw acoustic emission signal within a time window of ±100μs before and after the arc extinction moment. Perform three-level wavelet packet decomposition on this signal (using the db4 wavelet), and extract the wavelet packet coefficients of the 8th node in the 3rd level (corresponding to the highest frequency sub-band, e.g., 300-400kHz). Calculate the energy of this subband as the arc extinction sharpness; calculation formula: .

[0030] Efficiency coefficient calculation refers to fusing multidimensional feature parameters into a single quantitative index. For example, after eliminating dimensional differences through normalization, a weighted summation method is used to generate an efficiency value within the range of 0 to 1. The weight allocation can be dynamically adjusted according to the contribution of each feature parameter to regional degradation. In this embodiment, an efficiency coefficient between 0 and 1 is defined for each segment. (X represents L, M, R), quantifying the performance of this section during a single interruption.

[0031] The efficiency coefficient of the left section is: The first term in the above formula evaluates the quality of the arc initiation phase; the closer it is to 90°, the lower the score. The second term evaluates the initial energy impact and is an exponential decay function. This is a reference energy value, determined experimentally. In this embodiment, its value is 50 J. , As weight, + =1, in this embodiment , .

[0032] The efficiency coefficient of the intermediate section is: The first term in the above formula evaluates the speed of motion. This is the ideal speed reference value, which is 50 m / s in this embodiment. The second evaluation parameter, residence time, is an exponentially decaying function. This is a reference time; in this embodiment, it is 2ms. Weight . , , This refers to the duration of continuous burning of the electric arc within the intermediate section.

[0033] The efficiency coefficient of the right-side section is: The first metric evaluates the ability to build up pressure, and the second evaluates the crispness of arc extinction. Both are positively correlated with efficiency. and For reference, the former is taken as 50 MPa / s, and the latter as 1000; .

[0034] An independent performance degradation model refers to a mathematical relationship established for each segment, such as using an exponential function to describe the trend of performance coefficient decay with increasing number of breaks. The cumulative degradation can be extracted from the degradation curve through integral calculation or logarithmic transformation, reflecting the degree of fatigue accumulation of the material in that region.

[0035] The performance degradation model established in this embodiment is as follows: Where X represents the segment (L, M, R), and j is the number of operations. This is the initial efficiency coefficient, which is usually set to 1; This is the degradation rate coefficient, representing the natural logarithmic decrease in performance of section X for every unit of cumulative stress it experiences. Its unit depends on the cumulative stress. The units (e.g., J⁻¹, (Pa / s)⁻¹) are obtained by fitting accelerated life test data; Cumulative stress, representing the cumulative stress load borne by section X from operation 1 to operation j, has a different physical meaning depending on the section: calculated as follows: ; ; .

[0036] The cumulative degradation is then calculated using the following formula: Calculate the cumulative degradation of the system based on the cumulative degradation amount: ; The formula for predicting remaining useful life is as follows: .

[0037] Specifically, this method first establishes physical monitoring units through spatial division, ensuring each region corresponds to a specific degradation mechanism. In the left section, a high-frequency current sensor captures the current characteristics at the moment of contact separation, and combined with the arc morphology recorded by an optical sensor, the degree of ablation of the contact material by the arc-starting energy can be accurately calculated. In the middle section, a Hall sensor array reconstructs the arc trajectory by detecting changes in the magnetic field, and combined with the discharge phenomenon between the arc-extinguishing grids recorded by an ultraviolet sensor, the erosion effect of arc energy transfer efficiency on the grid coating can be assessed. In the right section, a pressure sensor monitors the transient process of pressure during the arc-extinguishing stage, and combined with the mechanical vibration signals captured by an acoustic emission sensor, the damage accumulation of the arc-extinguishing impact on the sealing structure of the arc-extinguishing chamber can be quantified.

[0038] After normalization, the characteristic parameters of each segment are fused into an efficiency coefficient using preset weights. For example, the left segment proportionally fuses the arc initiation phase angle deviation and initial arc energy; the middle segment weights the abnormal arc velocity values ​​and excessive residence time values; and the right segment combines the pressure rise rate and acoustic emission spectrum characteristics for analysis. The efficiency coefficient's time-varying curve is input into an exponential decay model, and linear regression yields the quantified value of the cumulative degradation in each segment.

[0039] Compared to existing technologies, traditional methods use a single cumulative electrical parameter value as the lifetime criterion, failing to distinguish the contribution of contact erosion to arc-extinguishing grid damage. This solution, through functional zone monitoring, can accurately identify specific areas leading to degradation. For example, when the cumulative degradation in the right-side section is significantly higher than in other sections, it indicates that decreased sealing performance of the arc-extinguishing cavity is the primary cause of failure. Furthermore, the independent modeling mechanism allows for setting differentiated failure thresholds based on the material properties of different sections, avoiding the sensitivity of a uniform threshold model to individual differences.

[0040] Through the above technical solutions, this application achieves a refined assessment of the internal state of the arc-extinguishing device. The functional zoning monitoring mechanism solves the problem of overall prediction ambiguity, enabling maintenance personnel to locate specific degradation areas. Multi-dimensional sensor data fusion overcomes the limitations of sensing single electrical parameters, improving the accuracy of state identification. The independent modeling method, by adapting to the degradation patterns of each section, enhances the model's robustness to individual differences, providing data support for differentiated operation and maintenance strategies.

[0041] This application further proposes that the sensor group in the left section includes a high-frequency current transformer and a high-speed optical sensor, wherein the high-frequency current transformer is installed on the conductive circuit adjacent to the moving and stationary contacts, and the high-speed optical sensor is aligned with the contact separation gap through an optical observation window.

[0042] The high-frequency current transformer is a sensor used to capture the transient current characteristics at the moment of contact separation. It can be implemented using a Rogowski coil or a fluxgate current sensor, and its installation position is close to the conductive circuit of the moving and stationary contacts, allowing direct coupling of current change signals. This arrangement effectively eliminates the influence of distributed line parameters on high-frequency signals, ensuring complete capture of the sudden current changes during the initial arc initiation. The high-speed optical sensor is an imaging device used to record the evolution of the arc morphology during contact separation. It can be implemented using a CMOS image sensor with a frame rate of at least 1 million frames per second. Its optical viewing window is made of high-temperature resistant quartz glass, and its mounting axis forms an angle of 30 to 60 degrees with the contact separation plane. This angle setting avoids interference from metal vapor on image quality while fully covering the dynamic changes in the contact separation gap.

[0043] Specifically, a high-frequency current transformer acquires current signals in the conductive circuit in real time through electromagnetic induction, with a frequency response range covering 10 kHz to 1 MHz, accurately capturing the high-frequency oscillation characteristics of the current at the moment of arc initiation. A high-speed optical sensor acquires image sequences of the contact separation gap through an optical observation window and extracts arc morphology parameters using a differential image processing algorithm. The two sensors achieve microsecond-level synchronous acquisition in the time dimension through a synchronous triggering device, forming an electromagnetic-optical joint observation field of the contact gap in the spatial dimension. Synchronous analysis of the current signal and optical images can establish the correspondence between the arc initiation phase angle and the initial arc morphology, providing cross-validation data for quantifying the degree of contact ablation.

[0044] Compared to existing technologies, traditional methods rely solely on the integral calculation of the arc current to estimate the arc ignition energy, failing to distinguish between the transient characteristics at the moment of contact separation and the steady-state arcing process. This proposed solution, through the coordinated monitoring of a high-frequency current transformer and a high-speed optical sensor, not only acquires the high-frequency current component during the arc ignition process but also directly observes the dynamic process of contact separation via optical imaging. This multi-physical quantity fusion monitoring method overcomes the limitations of single electrical signal analysis, enabling arc ignition energy calculation with a time resolution accurate to the microsecond level.

[0045] Through the above technical solution, this application achieves multi-dimensional and accurate monitoring of the transient process in the arc initiation region, solving the problem of incomplete capture of contact separation dynamic characteristics caused by the single sensor type in traditional methods. The spatially complementary layout of the high-frequency current transformer and the high-speed optical sensor enables the electromagnetic characteristics and physical deformation in the early stage of arc initiation to be recorded synchronously, providing a high-precision raw data foundation for subsequent calculation of the initial arc energy.

[0046] This application further proposes that the sensor group in the intermediate section includes a Hall sensor array and an ultraviolet sensor, wherein the Hall sensor array is arranged at a specific interval along the direction of arc movement, and the ultraviolet sensor is installed at an observation window that can cover the area of ​​the arc-extinguishing grid.

[0047] The Hall sensor array refers to multiple magnetic field detection units arranged along the arc's movement path, specifically using a linear arrangement spaced 5-15 mm apart. It detects changes in the magnetic field strength generated by the arc current, allowing real-time analysis of the arc's spatial distribution within the arc-extinguishing chamber. The ultraviolet sensor is a radiation detector based on ultraviolet photosensitive elements, specifically a silicon photodiode with a narrowband filter. It captures the 200-400 nm ultraviolet radiation generated by the arc in the arc-extinguishing grid region, accurately determining the contact state between the arc and the arc-extinguishing grid.

[0048] Specifically, during the circuit breaker's breaking process, as the arc migrates from the contact area towards the arc-extinguishing grid, the Hall sensor array calculates the arc head's trajectory within the arc-extinguishing chamber by detecting the temporal changes in the magnetic field strength at each node. For example, when the magnetic field strength of two adjacent Hall sensors reaches a preset threshold, it can be determined that the arc has reached that position, and the arc's velocity can be calculated using the time difference. Simultaneously, the ultraviolet sensor monitors the ultraviolet radiation intensity in the arc-extinguishing grid area in real time through an observation window. When a sudden change in a specific spectral intensity is detected, it indicates that the arc has entered the arc-extinguishing grid and begun to extinguish. After fusing the data from both sensors, the spatial migration characteristics and temporal evolution of the arc in the intermediate section can be acquired synchronously.

[0049] Compared to existing technologies, traditional methods only indirectly infer the arc motion state through arc voltage and current waveforms, failing to distinguish arc behavior at different locations within the arc-extinguishing chamber. This solution, however, achieves millimeter-level spatial resolution monitoring of the arc position using a Hall array, combined with direct optical detection of the arc-extinguishing grid area using an ultraviolet sensor, forming a multi-dimensional arc motion process sensing capability and solving the problem of missing state information caused by monitoring only a single electrical parameter.

[0050] Through the above technical solution, this application can accurately capture the dynamic migration process of the arc in the intermediate section, including the trajectory of the arc movement speed change and the time node of the arc extinguishing grid action, providing high-precision characteristic parameters for evaluating the performance degradation of the arc extinguishing device in the arc energy transfer stage, and effectively overcoming the shortcomings of traditional monitoring methods in sensing the internal physical process of the arc extinguishing chamber.

[0051] This application further proposes that the sensor group in the right section includes a dynamic pressure sensor and an acoustic emission sensor, wherein the dynamic pressure sensor is connected to the arc-extinguishing chamber cavity through a pressure guide hole, and the acoustic emission sensor is installed on the surface of the outer shell of the arc-extinguishing chamber.

[0052] The dynamic pressure sensor is used to detect dynamic changes in the internal pressure of the arc-extinguishing chamber. It can be implemented using a piezoresistive or piezoelectric sensor and is directly connected to the arc-extinguishing chamber cavity through a pressure-conducting hole to ensure the real-time and accurate transmission of the pressure signal. The acoustic emission sensor is used to capture high-frequency acoustic wave signals generated by mechanical vibrations during the arc-extinguishing process. It can be implemented using a resonant acoustic emission sensor and is installed on the outer surface of the arc-extinguishing chamber shell. The shell serves as the vibration transmission medium, preventing the sensor from directly contacting the high-temperature area.

[0053] Specifically, the dynamic pressure sensor is connected to the arc-extinguishing chamber via a pressure-guiding hole, enabling it to directly acquire the dynamic characteristics of pressure changes within the chamber during arc extinguishing and reflect the transient response of the pressure build-up process in real time. The acoustic emission sensor, mounted on the outer shell of the arc-extinguishing chamber, effectively identifies the mechanical impact characteristics during arc extinguishing by capturing the high-frequency acoustic emission signal generated by the vibration of the metal grid at the moment of arc extinguishing. The interconnected design of the pressure-guiding hole protects the pressure sensor from the high temperature of the arc while ensuring the fidelity of the pressure signal; the surface mounting method utilizes the high-frequency vibration transmission characteristics of the metal shell to achieve non-invasive detection. Data from both sensors are acquired synchronously over time, forming a collaborative monitoring of the pressure and vibration fields, constructing a multi-dimensional characteristic representation of the arc extinguishing process.

[0054] Compared with existing technologies, traditional methods only indirectly infer the arc extinction state through arc voltage or current signals, and cannot directly obtain information on pressure changes and mechanical vibrations inside the arc extinguishing chamber. This solution, through the combined arrangement of dynamic pressure sensors and acoustic emission sensors, achieves for the first time the synchronous detection of pressure fluctuations and high-frequency mechanical vibrations during the arc extinguishing process, and fully captures the dynamic characteristics of the arc extinguishing stage from the perspective of physical field coupling.

[0055] Through the above technical solution, this application solves the problem of the single dimension of traditional arc extinguishing characteristic detection, and realizes the coordinated perception of pressure fluctuations and high-frequency mechanical vibrations inside the arc extinguishing chamber. The dynamic pressure sensor directly monitors the pressure changes in the chamber, accurately reflecting the gas expansion and compression effects during the arc extinguishing process; the acoustic emission sensor indirectly obtains the mechanical impact state of the metal grid through the shell vibration signal. The combination of the two provides multi-dimensional data support for evaluating the performance degradation of the arc extinguishing device, and significantly improves the accuracy and reliability of the life prediction model.

[0056] This application further proposes a technical solution to extract the arc initiation phase angle and initial arc energy as characteristic parameters in the left segment. The arc initiation phase angle is obtained by analyzing the phase relationship between the current signal and the voltage signal, and the initial arc energy is obtained by integrating the arc energy within a specific time window during the initial stage of arc initiation.

[0057] The arc initiation phase angle refers to the phase difference between the current and voltage at the instant of contact separation. This can be achieved by extracting the zero-crossing time difference within the power frequency cycle using a phase-locked loop circuit or digital signal processing algorithms. This parameter reflects the position of the contact separation moment within the AC cycle and directly affects the initial energy injection characteristics of the arc. The initial arc ignition energy refers to the cumulative energy value within a preset time window during the arc initiation process. This can be achieved by measuring the product of the arc current and voltage using a Hall sensor and then integrating the results over time. This parameter characterizes the thermal stress input intensity during the arc initiation stage and is directly related to the degree of contact material ablation.

[0058] Specifically, during circuit breaker disconnection, a high-frequency current transformer acquires the current waveform at the instant of contact separation in real time and simultaneously measures the circuit voltage signal. By comparing the time difference between the current zero-crossing point and the voltage zero-crossing point, the phase position of the arc initiation within the AC cycle is calculated. Simultaneously, within the time window after contact separation, the product of the arc current and voltage is numerically integrated to obtain the total energy released during this stage. These two parameters, from the perspectives of electrical timing characteristics and energy accumulation effect, respectively, construct a quantitative index system reflecting the dynamic characteristics of the arc initiation process.

[0059] Compared with existing technologies, traditional methods assess the arc initiation process using only a single parameter, such as the effective value of current or the amplitude of voltage. This fails to distinguish the changes in arc characteristics caused by phase differences, nor can it reflect the impact of short-term energy accumulation on contact erosion. This proposed solution, through phase relationship analysis and time window integration, achieves simultaneous capture of the temporal and energy characteristics of the arc initiation process, thus solving the problem of missing dimensions in single electrical parameter monitoring.

[0060] Through the above technical solution, this application effectively improves the monitoring accuracy of the dynamic characteristics of the arc initiation process and establishes a quantitative evaluation index directly related to the degree of contact ablation. By simultaneously acquiring phase position information and energy accumulation data, the characteristic differences of the arc initiation process under different load conditions can be accurately identified, providing a reliable data foundation for subsequent performance degradation analysis.

[0061] This application further proposes characteristic parameters for the intermediate section, including arc speed and dwell time within the section. The arc speed is obtained by analyzing the rate of change of arc position, and the dwell time within the section is obtained by calculating the length of time the arc exists within the section.

[0062] The arc velocity refers to the migration rate of the arc between the arc-extinguishing grids. Specifically, it can be calculated using magnetic field strength variation data collected by a Hall sensor array, calculated as the ratio of the trigger time difference between adjacent sensor signals to a known distance. This parameter reflects the instantaneous impact intensity on the arc-extinguishing material during the arc energy transfer process. The dwell time within the zone refers to the total duration for which the arc maintains its motion in the intermediate section. Specifically, it can be obtained by combining the effective duration of the ultraviolet sensor signal with arc position trajectory analysis. This parameter characterizes the continuous cumulative effect of thermal stress on the arc-extinguishing grids.

[0063] Specifically, the Hall sensor array is arranged along the axial direction of the arc-extinguishing chamber at preset intervals. When the arc passes through different sensor positions, the instantaneous value of the arc's velocity is obtained by recording the trigger timestamps of each sensor and calculating the ratio of the time interval between adjacent sensors to the fixed interval. An ultraviolet sensor continuously monitors the arc radiation intensity. When the signal amplitude exceeds a preset threshold, the arc is determined to have entered the intermediate section; when the signal falls below the threshold, the arc is determined to have left the section. The time difference between these two values ​​is the dwell time within the section. By synchronously acquiring arc velocity and dwell time data, a correlation model between the arc's dynamic migration characteristics and the degradation of the arc-extinguishing grid material can be established, providing a quantitative basis for assessing the performance degradation in the intermediate section.

[0064] Compared to existing technologies, traditional methods rely solely on arc current and voltage signals to estimate overall arc energy, failing to distinguish the impact of arc dynamics in different sections on device lifespan. This solution, by introducing dual-dimensional monitoring of arc velocity and residence time, can accurately capture the arc migration efficiency and energy distribution characteristics between arc-extinguishing grids, overcoming the technical limitation that a single electrical parameter cannot reflect local thermal stress accumulation.

[0065] Through the above technical solution, this application achieves dynamic monitoring of the arc movement process in the middle section of the arc extinguishing device, solving the problem of life assessment bias caused by the single sensing dimension in traditional methods. By quantifying the arc migration rate and residence time, the local degradation trend of the arc extinguishing grid material can be accurately identified, providing section-specific degradation data support for predicting the remaining life of the device.

[0066] This application further proposes characteristic parameters for the right-side section, including the rate of increase in air pressure and the sharpness of arc extinction. The rate of increase in air pressure is obtained by analyzing the rate of change of the air pressure signal, and the sharpness of arc extinction is obtained by frequency domain analysis of the acoustic emission signal.

[0067] The pressure rise rate refers to the pressure gradient within the arc-extinguishing chamber over time. This can be achieved by using a dynamic pressure sensor to collect pressure signals and calculating the pressure increment per unit time. This parameter reflects the dynamic establishment of the pressure field during the arc-extinguishing medium's recovery process and directly affects the arc energy dissipation efficiency. The arc-extinguishing sharpness refers to the high-frequency mechanical vibration energy released at the moment of arc extinguishing. This can be achieved by using an acoustic emission sensor to collect vibration signals and extracting the energy proportion of a specific frequency band through a fast Fourier transform. This parameter characterizes the steepness of the arc current cutoff and reflects the arc-extinguishing chamber's ability to suppress residual arc energy.

[0068] Specifically, a dynamic pressure sensor and an acoustic emission sensor are installed on the right side of the arc-extinguishing chamber. The dynamic pressure sensor is connected to the arc-extinguishing chamber cavity through a pressure guide hole to monitor the pressure change trend of the cavity in real time during the interruption process. By differentially calculating the pressure difference between adjacent sampling points, a quantitative index of the pressure rise rate is obtained, which is used to evaluate the flow characteristics of the arc-extinguishing medium under the action of a pressure gradient. The acoustic emission sensor is installed on the surface of the arc-extinguishing chamber shell to collect the stress wave signal generated when the arc is extinguished. After performing spectral analysis on the signal, the energy integral value of the high-frequency band is extracted as the arc-extinguishing sharpness parameter, which reflects the energy release intensity at the moment of arc current cutoff. By simultaneously monitoring the dynamic characteristics of pressure and mechanical vibration characteristics, the arc-extinguishing efficiency can be comprehensively evaluated from two dimensions: pressure field reconstruction and energy dissipation.

[0069] Compared to existing technologies, current methods typically determine the arc extinction state solely based on arc voltage and current waveforms, failing to capture information on internal pressure field changes and mechanical vibrations within the arc extinguishing chamber. This proposed solution, by introducing dynamic air pressure and acoustic emission signals, directly captures the dynamic characteristics of the pressure build-up process and the mechanical impact features of arc energy dissipation, thus resolving the bias in arc extinguishing performance assessment caused by traditional methods relying on a single electrical parameter.

[0070] Through the above technical solution, this application realizes the synchronous monitoring of the dynamic characteristics of the pressure field and the mechanical vibration energy of the right section of the arc extinguishing chamber. By combining the parameters of the air pressure rise rate and the arc extinguishing sharpness, the recovery strength of the arc extinguishing medium and the arc energy dissipation efficiency are accurately quantified, solving the problem that traditional methods cannot effectively evaluate the dynamic characteristics of the arc extinguishing process, and providing a multi-dimensional state assessment basis for the life prediction of the arc extinguishing device.

[0071] This application further proposes a weighted fusion method for calculating the efficiency coefficient, which normalizes each characteristic parameter and then fuses them according to a predetermined weight to obtain an efficiency coefficient value between 0 and 1.

[0072] The weighted fusion method refers to combining multiple feature parameters into a single evaluation index using mathematical methods. Specifically, it can be achieved using a linear weighted summation method, with different parameters assigned weights based on their impact on efficiency. Normalization is a data preprocessing method that eliminates differences in the dimensions of different feature parameters. Specifically, it can be achieved using the range method or the standard deviation method, ensuring that all parameters are within the same numerical range. Predetermined weights are proportional coefficients reflecting the degree of influence of feature parameters on section efficiency. These can be determined through expert experience or machine learning algorithms, and the weight allocation must satisfy the differences in the contribution of each parameter to section degradation. The efficiency coefficient value is a quantitative indicator characterizing the work efficiency of a section. It is achieved by mapping the weighted calculation results to the 0-1 range; the closer the value is to 1, the closer the efficiency is to the ideal state.

[0073] Specifically, in the life prediction process of the arc extinguishing device, the raw signals collected by sensors in each section are processed into multi-dimensional parameters after feature extraction. Since different parameters have different physical meanings and dimensions (e.g., arc ignition energy is measured in joules while the rate of pressure rise is measured in Pascals per second), normalization is required to eliminate these dimensional differences. The normalized parameters are then linearly superimposed according to predetermined weights. The weight allocation can be dynamically adjusted based on the equipment type or operating environment; for example, the weight of the arc velocity's influence on the efficiency of the intermediate section can be set higher than that of other parameters. The final efficiency coefficient value serves as a standardized evaluation benchmark, providing a unified input for subsequent degradation modeling and ensuring the comparability of evaluation results for different sections and different equipment.

[0074] Compared to existing technologies, traditional methods rely solely on a single arc energy parameter for lifetime assessment, failing to reflect the state differences between different areas within the arc-extinguishing chamber. This solution, through multi-dimensional feature fusion, can simultaneously capture the impact of multiple factors such as contact erosion, arc movement, and gas pressure changes on performance. The weighting mechanism can be adaptively adjusted for different equipment material characteristics or manufacturing tolerances, avoiding misjudgments caused by fixed thresholds.

[0075] Through the above technical solution, this application solves the problem of evaluation bias caused by the single perception dimension of traditional methods, realizes the fine monitoring of the degradation status of each functional area inside the arc extinguishing device, and enhances the adaptability to individual differences through the weighted fusion method, thereby improving the accuracy and reliability of life prediction.

[0076] This application further proposes an efficiency degradation model that adopts an exponential degradation form, which correlates the efficiency coefficient of a section with the exponential degradation relationship of the cumulative stress of the section, and obtains the linearized cumulative degradation by taking the natural logarithm.

[0077] The exponential decay form refers to using a mathematical exponential function to describe the nonlinear decay law of material performance with stress accumulation. Specifically, it can be achieved by establishing a negative exponential relationship between the efficiency coefficient and cumulative stress. This form can accurately characterize the physical essence of failure mechanisms such as metal oxidation ablation and insulation material carbonization. The section efficiency coefficient is a numerical performance index obtained by fusing feature parameters extracted from sensor data. Specifically, it can be calculated using a normalized weighted fusion method. This coefficient is used to quantify the real-time working efficiency of each functional section of the arc-extinguishing device. The cumulative stress refers to the sum of physical or electrical stress borne by the functional section during multiple interruption operations. Specifically, it can be calculated by accumulating the abnormal values ​​of feature parameters generated during each interruption. This parameter reflects the driving factors of material performance degradation. The natural logarithm transformation refers to mathematically transforming the exponential decay relationship to obtain a linear relationship. Specifically, it can be achieved by taking the natural logarithm of both sides of the exponential equation between the efficiency coefficient and cumulative stress. This transformation simplifies the calculation of cumulative degradation and reveals the intrinsic correlation between stress accumulation and performance degradation.

[0078] Specifically, addressing the nonlinear degradation phenomena such as oxidation of metal components and carbonization of insulating materials in different functional sections of the arc-extinguishing device, an exponential decay relationship between the efficiency coefficient and cumulative stress is established. This allows for a precise description of the accelerated degradation characteristics of material properties with increasing stress. After each interruption operation, the efficiency coefficient of each section is calculated based on real-time sensor data and substituted into the exponential equation to deduce the cumulative stress value. A natural logarithmic transformation converts the originally nonlinear exponential relationship into a linear one, enabling the cumulative degradation to be directly calculated via linear regression. This reduces model complexity while preserving individual differences caused by different material batches or manufacturing tolerances.

[0079] Compared to existing technologies, traditional methods use linear cumulative models to directly treat stress superposition as the degradation factor, neglecting the nonlinear characteristics of material performance degradation. This proposed solution, however, uses an exponential function model, which better aligns with the physical laws governing accelerated material performance degradation during arc ablation. Furthermore, the natural logarithmic transformation not only simplifies model calculations but also allows for adaptive adjustment of the model parameter k through linearization, effectively accommodating variations in performance degradation rates caused by manufacturing differences in different arc-extinguishing devices.

[0080] Through the above technical solutions, this application can accurately quantify the actual degradation degree of each functional section of the arc extinguishing device, accurately reflect the nonlinear change law of material properties through the exponential decay model, and establish an analytically calculable linear relationship by using natural logarithmic transformation, so that the model can not only characterize individual differences but also have the computational efficiency required for engineering applications, and finally achieve accurate life prediction for the functional sections of the arc extinguishing device.

[0081] This application further proposes a proportional calculation method for predicting remaining lifetime, which divides the difference between the cumulative degradation of the system and the failure threshold by the failure threshold to obtain the percentage of remaining lifetime. When the cumulative degradation of a certain segment reaches its maximum value, a specific warning message for that segment is output.

[0082] The proportional calculation method refers to quantitatively linking the cumulative degradation of the system with the failure threshold through mathematical operations. Specifically, it can be achieved using the formula (cumulative degradation - failure threshold) / failure threshold. This method eliminates the impact of individual equipment differences on lifespan assessment through relative value calculation. The specific early warning information refers to the directional alarm signal generated for the segment with the highest cumulative degradation. This is achieved by comparing the real-time values ​​of the cumulative degradation in three segments and triggering the alarm code corresponding to the segment with the highest value. This mechanism directly links the most severely degraded area with maintenance decisions.

[0083] Specifically, after each interruption operation, the cumulative degradation of the system is calculated as the maximum value of the cumulative degradation in the three sections. The remaining lifespan percentage is converted into a quantifiable indicator by calculating the difference between the current cumulative degradation and a preset failure threshold, and then dividing by the failure threshold. For example, when the failure threshold is 100 and the current cumulative degradation is 80, the remaining lifespan percentage is (100-80) / 100 = 20%. Simultaneously, the system continuously tracks the real-time values ​​of the cumulative degradation in each section. When the value of a certain section exceeds that of other sections, a warning message containing the location identifier of that section is automatically generated. This calculation method eliminates absolute value differences through ratio calculations, making lifespan predictions comparable for different batches or models of equipment; the warning message generation mechanism focuses maintenance efforts on the arc-extinguishing device area where actual degradation is most severe.

[0084] Compared to existing technologies, traditional methods use fixed thresholds to determine the end of the lifespan, which cannot distinguish the degradation differences between different sections within the arc-extinguishing device, and the threshold setting ignores the individual characteristics of the equipment. This solution transforms the lifespan prediction into a relative value assessment through proportional calculation, allowing the prediction results to automatically adapt to the actual operating conditions of different equipment; through a specific early warning mechanism, while outputting the overall lifespan percentage, it accurately identifies the functional sections of the arc-extinguishing device that require priority maintenance.

[0085] Through the above technical solutions, this application achieves differentiated assessment of the degradation degree of different sections of the arc extinguishing device, solving the problem of fuzzy prediction objects in traditional methods; improves the adaptability of life prediction results to individual equipment differences by using proportional calculation methods; and provides maintenance personnel with clear fault location basis by outputting specific early warning information, reducing the blindness of equipment maintenance.

[0086] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

[0087] As used in the specification and claims, certain terms refer to specific components. Those skilled in the art will understand that hardware manufacturers may use different names to refer to the same component. This specification and claims do not distinguish components based on differences in name, but rather on differences in function. The term "comprising" throughout the specification and claims is an open-ended term and should be interpreted as "comprising but not limited to." "Approximately" means that within an acceptable margin of error, those skilled in the art can solve the technical problem and substantially achieve the technical effect within a certain margin of error.

[0088] The foregoing description illustrates and describes several preferred embodiments of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the inventive concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker, characterized in that, Includes the following steps: (a) The arc-extinguishing chamber is divided into three functionally independent sections along the direction of arc movement: the left section corresponds to the arc-starting area where the moving and stationary contacts separate, the middle section corresponds to the arc movement and energy transfer area, and the right section corresponds to the arc extinguishing and pressure building area. (b) Deploy a dedicated sensor array in each section, wherein the left section is configured with a sensor array for monitoring arc initiation characteristics, the middle section is configured with a sensor array for tracking arc motion characteristics, and the right section is configured with a sensor array for detecting arc extinction characteristics. (c) Collect the output signals of each sensor during each interruption operation and extract the feature parameters of each segment. The feature parameters related to the arc initiation process are extracted from the left segment, the feature parameters related to the arc movement process are extracted from the middle segment, and the feature parameters related to the arc extinguishing process are extracted from the right segment. (d) Based on the characteristic parameters of each segment, calculate the efficiency coefficient of the left segment, the efficiency coefficient of the middle segment, and the efficiency coefficient of the right segment respectively; (e) Establish an independent performance degradation model for each segment and calculate the cumulative degradation of each segment; (f) Take the maximum value of the cumulative degradation of the three sections as the cumulative degradation of the system, predict the remaining lifetime based on the comparison between the cumulative degradation of the system and the failure threshold, and identify the section with the most severe degradation.

2. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The sensor group in the left section includes a high-frequency current transformer and a high-speed optical sensor. The high-frequency current transformer is installed on the conductive circuit adjacent to the moving and stationary contacts, and the high-speed optical sensor is aligned with the contact separation gap through an optical observation window.

3. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The sensor group in the middle section includes a Hall sensor array and an ultraviolet sensor. The Hall sensor array is arranged at a specific interval along the direction of arc movement, and the ultraviolet sensor is installed at an observation window that can cover the arc-extinguishing grid area.

4. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The sensor group in the right section includes a dynamic pressure sensor and an acoustic emission sensor. The dynamic pressure sensor is connected to the arc-extinguishing chamber cavity through a pressure guide hole, and the acoustic emission sensor is installed on the surface of the outer shell of the arc-extinguishing chamber.

5. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The characteristic parameters of the left segment include the arc initiation phase angle and the initial arc energy. The arc initiation phase angle is obtained by analyzing the phase relationship between the current signal and the voltage signal, and the initial arc energy is obtained by integrating the arc energy within a specific time window during the initial arc initiation.

6. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The characteristic parameters of the intermediate section include the arc movement speed and the dwell time within the section. The arc movement speed is obtained by analyzing the arc position change rate, and the dwell time within the section is obtained by calculating the length of time the arc exists within the section.

7. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The characteristic parameters of the right-side section include the rate of increase of air pressure and the sharpness of arc extinction. The rate of increase of air pressure is obtained by analyzing the rate of change of air pressure signal, and the sharpness of arc extinction is obtained by frequency domain analysis of acoustic emission signal.

8. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The efficiency coefficient calculation adopts a weighted fusion method, which normalizes each feature parameter and then fuses them according to a predetermined weight to obtain an efficiency coefficient value between 0 and 1.

9. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The efficiency degradation model adopts an exponential degradation form, which correlates the efficiency coefficient of a section with the exponential degradation relationship of the cumulative stress of the section, and obtains the linearized cumulative degradation by taking the natural logarithm.

10. The method for predicting the lifespan of the arc-extinguishing device of a low-voltage circuit breaker according to claim 1, characterized in that, The remaining lifetime prediction uses a proportional calculation method, which divides the difference between the cumulative degradation of the system and the failure threshold by the failure threshold to obtain the percentage of remaining lifetime. When the cumulative degradation of a certain segment reaches its maximum value, a specific warning message for that segment is output.

Images